Sudden cardiac death is among this nation's most serious and persistent public health problems. Some 351,000 Americans experience a sudden cardiac arrest outside of the hospital each year. On average, less than 7% survive to hospital discharge. The electrocardiogram (ECG) contains information that is used to guide decision making during the treatment of cardiac arrest. When the ECG rhythm is ventricular fibrillation (VF) defibrillation is recommended. However, all VF is not clinically the same and this variability can be seen in the morphology of the VF waveform. We have developed quantitative ECG measures (QECG) that can differentiate VF of various durations. Specific Aims: Through our ongoing investigation (NHLBI contract 1R21HL104440-01A1) we have developed a working rapport with the Resuscitation Outcomes Consortium (ROC). We now seek to greatly adapt and extend the work we have begun together. Using the data management and analytical platform that we have developed, we will construct an annotated multi-parameter database of physiologic signals, in a universal format, that will be both unique and the largest repository of its kind. Ai 1: We will describe the relationship between QECG measures, CPR quality measures, and resuscitation outcomes, providing electrophysiologic insight into the quality and quantitative effectiveness of CPR. Aim 2: We will refine the use of QECG measures for predicting defibrillation success by deriving the optimum cutpoints for each measure, and validating these with a randomly sampled test set of data. Aim 3: We will compare the QECG measures in order to determine whether any measure is superior to the others in terms of its ability to guide defibrillation attempts and other therapies. Aim 4: We will conduct the first large scale study of the relationship between CPR quality measures and the outcomes of patients whose initial ECG rhythm is not VF, i.e. cases in which the first rhythm is PEA, asystole, or determined to be a non-shockable rhythm by an AED (NS-AED). Innovation: This project will be the first to definitively establish the physiologic relationship between the quality of CPR and the change in the ECG in humans during ongoing clinical trials, coupling these findings with patient outcomes. Since the first submission, we have built a new analytic platform in MATLAB which is also highly innovative. Finally, additional innovation has been added in that we will be the first to directly compare primary VF to secondary VF on a large scale basis, as well as closely examining the effects of CPR quality on non- VF ECG rhythms (the oft-overlooked rhythms of PEA and asystole). Translational Potential: The natural extension of this work will be to use QECG measures to guide therapy of cardiac arrest in real- time. The ability to calculate these measures in real-time is well established and has been cleared by the FDA. This study could lead to the next ROC and/or other multi-centered clinical trial.